Can Save You Money
Helen Mallovy Hicks
In this recovering economy, making sure you have accurate business modelling and forecasting tools is more important than ever before. In this episode of Strategy Talks, guest Sean Rowe talks about the difference good business modelling practices can make to your company's bottom line.
Announcer: Welcome to Strategy Talks, the business podcast series by PricewaterhouseCoopers Canada. Hosted by Helen Mallovy Hicks, National Leader of PwC’s Dispute Analysis and Valuations Practice, and Calum Semple, an Operations and Consulting Partner. This interview series, featuring new topics and guests every episode, is designed to valuable insight into some of today’s hottest issues affecting your business.
Helen: Now that we’re beginning to see signs in the economy improving, there is a general expectation out there that mergers and acquisitions activities are started to increase again. Financial models have a very important role to play in all of this. Joining us today is Sean Rowe, a Vice President at PwC and Leader of our Business Modeling Services group. He is here to discuss why business modelling may be essential to your company. Welcome Sean.
Helen: So Sean, maybe we should start off with just an explanation. What is business modelling, what do you and your team do?
Sean: What we are really focused on is delivering independent advice to clients, either through assessing their models, taking their existing models and putting it through our proprietary software and looking for potential errors in the model, or we are working with clients to either develop their models or help them improve their models. Anytime companies are looking to do an acquisition, looking to make an investment, generally that’s supported by an Excel model and that’s where we can help clients.
Helen: Do we do the full design build?
Sean: Absolutely. We have a 5-phased approach to building financial models that we work with clients and our phases are really designed to help them control the process and make sure that the outputs are exactly what they need to make the decision.
Helen:In addition to model builds, I believe your team also uses proprietary software to do model analysis. Could you tell our listeners more about that?
Sean: What our software does, it really goes through a model and it looks for hard coded entries or areas where they have just basically miscoded formula. It also allows us to look at multiple versions of Excel models. So, if I have reviewed a model, I pass it back to the client, they have made a series of changes, I can isolate those changes and just check those changes. It is a very efficient process. It also allows us to drill into certain macros and isolate potential errors in a cost effective manner.
Calum: So, it is somewhat like a diagnostic. Like when I get my car checked at the dealer? They plug my car and it spits out where it might have potential problems?
Calum: What are the typical findings when you run this diagnostic? I imagine it’s all over the map, but are there some common ones that people kind of fall down on all the time?
Sean: We’ve found, looking at a valuation model, we found errors that basically doubled the value of the company.
Calum: Better than cutting it in half, right?
Sean: Except for if you can’t afford the company that you are pursuing. If you thought that this company was worth a million dollars and it turned to be worth 10 million dollars and you only had a million to spend, you have wasted a lot of time and energy. So getting us involved earlier in the process is very important.
Helen: Sean, do you usually find errors in models or issues? Does this come from small unsophisticated clients? Where do you find errors and with who?
Sean: I’ve reviewed models from investment banks, from pension funds, from large corporate clients and from small private clients. There are errors in all models. Modelling errors, some of the ones that we find, input errors. Where a function should be automated, somebody has hardcoded in a number. You would never see that unless you went line by line, cell by cell. You are looking at a discount of cash flow, everything looks honky-dory and somebody changes an assumption, that cell number changes. So you’ve got a huge error. Linking, multiple inputs for the same assumption, those are all typical common errors that we see and are easily spotted and addressed.
Helen: That’s amazing. That’s very interesting.
Sean: It really boils down to where you want to spend your time and money in building a model. If you have investment bankers build a model, some investment bankers are great, some it’s just not their core competency.
Calum: So, do organizations in management out there now get the significance of having a model that’s sound so the fundamental are there? And if they do, has that change the business environment from, say, five years ago?
Sean: Going back maybe five years ago, model reviews were very important for infrastructure place. Most people that were willing to pony-out money for infrastructure assets would always get a model review done, same is true today. Where we’re seeing companies pay more attention, given the economic downturn, CFOs are being tapped on the shoulder, and really watched, to make sure that they are managing their risk of the organization. Boards have a heightened sensitivity and we’re seeing companies now before they pony-up the cash to make investments, they’re really looking at, “Does this cash flow, it makes sense to me, but is it correct? Is this model doing what it says it’s doing, ” and they’re coming to people like PwC to really help them and understand what is in the model.
Calum: It is interesting that the infrastructure plays have been there for a number of years. Why do you think that would be the case? Is it just because of the heightened sensitivity of the infrastructural governance involved? Bigger dollars perhaps?
Sean: It’s bigger dollars, it’s discounted cash flows, it’s long periods of time, they’re very sensitive to assumptions, they’re very detailed models. They’ve always seen the value. I think companies are starting to recognize there is value in getting someone else to look at your model, irrespective to who’s developed it. In the times of resource constraints, companies are also recognizing that they don’t want their people building models, they want them doing value-add activities for the company.
Helen: What kind of resources do we have to build these models?
Sean: We have numerous individuals who have gone through training courses that we have internally at PwC. They have built numerous models. If you think of what PwC does, most of what PwC does is based on financial models, especially in the Valuations group and the Corporate Finance group. We have a strong skill set in making sure models are done right because our brand is behind the output.
Calum: So, when you are evaluating models, I understand that diagnostics are very formula driven. What about an assessment from an analytical perspective. If you think about a company in industry X versus a company in industry Y, two very different businesses, two very different environments. What do we bring to the table to help people understand these businesses and support our evaluation model?
Sean: I think that’s a great question. One of the key advantages that we have over an Excel model or who sits in a office, is we have a breath of industry expertise so going and looking at an Oil and Gas model, we can bring in an Oil and Gas Subject Matter Expert to look at the structure of the model, to look at the logic of the key assumptions and to really help clients understand where risks may be.
Helen: So Sean, maybe you can spend some time sharing the elements of our modeling process.
Sean: We follow a 5-phased approach that really looks at scoping the model which is sitting down with all stakeholders that are going to use the model, all the people that have input into the model and all the people that are going to use the output from the model to really understand from their perspective what is important, what are key value drivers and what is the output that they really want to see. The next step is, we really sit down with them and we almost whiteboard how the model is going to look, how‘s it going to work, and how’s it going to function. So, we specify what the outputs are going to look like, where the inputs are going to come from, and then we go away and we design it and we build it as the next couple of steps.
Finally, the most important step is that we test the model. We then put the model through rigorous process, the same process we use for model review to make sure the model is doing what it says it was doing and then we also encourage our clients to go and independently test the model so that they do have a second test of the model. Those five phases, from a client’s perspective, they are engaged in each phase. It really works so that they can get the proper output in a cost effective manner.
Calum: Given the current state of the economy, the increase emphasis on governance, do you see more pressure from outside investors to conduct this type of analysis in a more productive way?
Sean: Absolutely. If you think about the amount of money that is invested on doing due diligence on the balance on sheet, due diligence on the latest 12-months earnings, and you look at the amount of diligence that is done into the forecast and you think value is perspective, not retrospective. In the foreseeable future, I think, we will start to see companies pay more attention to what they expect to get out of an acquisition and looking at the forecast with the same scepticism as they have with the balance sheet and the latest 12-months earnings.
Calum: What’s really becoming more of a tool to guide your investment decisions where as before, I guess, they did use it for that, but maybe didn’t dive in as deeply as they should have or certainly as they need to going forward.
Sean: I think the implicit assumption was that Excel got it right. I have seen a lot of models where Excel always calculated it right, but, they underlying fundamentals were not right.
Calum: That’s very interesting because if you think about it as a retail investor, you rely on a series of checks and balances, financial statements and so forth, but as you say, value is perspective, not retrospective. There isn’t that checking balance going forward, so somebody can step off a cliff and not even realize it until they’ve hit the bottom.
Sean: I think you’ve seen that in the market, there’s been a lot of goodwill write-offs. Some people over paid and maybe some of those goodwill write-offs resulted in, you know, they paid too much because they thought the model was perfect and there are fundamental errors in some of the models.
Calum: Are we seeing boards becoming more diligent and basically saying that we want those extra set of eyes looking at this?
Sean: I think that at this point, we’re seeing CFOs trying to manage the risk and the pressure that the boards are putting on the CFOS, obviously they have to go out and manage the risk versus reward and I think CFOs are really driving the initiative, with the pressure from the boards. Right now,it’s more management , making sure that when they are going to step off the cliff, they want to make sure that they’ve got all information that they can possibly get.
Helen: What are we seeing in the private companies’ space? Are private companies using our business models in services, and if so, how would they be using them?
Sean: Absolutely. Clients are looking at deals across the spectrum and private clients are just as concerned about making sure that they balance their risk versus reward. Where clients are sensitive to fees, we work with our clients to really tailor an approach that works for them. In some situations they may not want to engage us to do a model build, but they may want to draw on our expertise just for advice. So I am looking at this module in an Excel model, and they’ll come to us and seek us put just to help them out a specific piece of the model.
Helen: I guess what you’ve said earlier, as risk management and resource constraints are probably the two main reasons we get called and in a private company, resources are certainly at a premium and they probably don’t have the skills.
Sean: In some situations, they also draw on us for our industry expertise. So, they want the advice on the model could also bring in a little industry expertise that they don’t have, if they are looking at going outside what they do on a day-to-day basis. That’s where we can really add value in a cost-effective manner.
Helen: You’ve told us some interesting stories about where you’ve found errors in models. Any other modelling war stories?
Sean: In one specific model, we were looking at a, it’s a little bit technical, but we were looking at a discounted cash flow for an entity that had tax losses. It was a 5-year model. The implicit assumption throughout the entire cash flow period, there were not going to be any taxes paid, which included into the terminal value calculation which is for perpetuity. So, effectively what they’ve done, they’ve modeled in a non-taxable price for a company that was really going to be taxable after year six. So they dramatically overpaid. This was an investment that they made, that they had modeled in, assuming that they were never going to pay taxes for the entire life of the company. When we pick it up and we looked at it, it was very obvious to us that they taxes hadn’t been modeled properly. If you think about terminal value, it’s in that 60+ percent range of the total value.
Helen: Right, so taking taxes out of the terminal value...
Helen: Huge chunk.
Sean: Huge chunk. I mean there are endless examples of picking up models and looking at models. Another one was, this was an acquisition of a public company. What this model had done was modeled in the share price, but the share price had multiple inputs throughout the model and it was updating real time based on the current share price. All except for two share prices. When the share price dropped, half the model was working, but half of it wasn’t.
Helen: These models that we look at, have they already been checked by our clients or is part of their problem is that they’re just not checking?
Sean: I think part of the problem is that people are relying on the individuals who are building the models who generally very competent, but in anything you need four sets of eyes to really be able to pick it up. Most clients don’t have tools and analytical software programs that will really go through a model in an effective way and you are really left going through an Excel file, line-by-line, code-by-code, and that’s really tedious and it’s not very effective. Frankly, once you’ve been through three tabs, you are going to get pretty tired, right? If the error is on the fourth tab, you may not catch it.
Calum: Well, Sean thanks for coming in today and shining a light on business modelling. It sounds like it can have an enormous impact on your business. To learn more about business modelling, please visit our webpage at pwc.com/ca/modelling.
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